To solve a real-world business problem using a Large Language Model (LLM) you need 3 things: A base LLM, for example, a proprietary model like GPT-3 or a fully open-source one like Dolly. An algorithm that fine-tunes the model parameters using a private dataset, so the model performs the task you want it to perform. A private dataset for the …
Training Machine Learning models inside notebooks is just one step to building real-world ML services. And as exciting as it is, it brings no business value unless you deploy and operationalize the model, as a real-world ML app. In this article, you will learn how to transform an all-in-one Jupyter notebook with data preparation and …
3 steps to transform an ML prototype into a real-world ML app Read More »
Real-time ML is a fascinating topic, which I wanna go deeper into in the following weeks and months. Because of this, I started creating a sequence of small projects where I build real-time products, beginning with a real-time feature engineering pipeline. Real-time feature engineering A real-time feature pipeline is a program that ingests real-time raw data (e.g. …
No more reading blog posts. It is time to forecast for real. 😎 Here is a project you can build. “Let’s predict taxi demand in NYC” Let’s create a predictive model to forecast the number of taxi rides that will happen in Manhattan (New York City) per hour (e.g. tomorrow between 5 PM and 6 …
Reading blog posts about multi-billion-parameter Language Models is very cool. However, building real-world NLP products from these models is where the real business value is. And this is what companies look for in the job market. So, here is a PRO project you can build. “An app that recommends what ML paper to read” Imagine …
Let’s build a Machine Learning service to predict the Air Quality Index (AQI) in your city in the next 3 days, using a 100% serverless stack. You will learn a lot, AND you will build something useful for society. Win-win These are steps to build this ↓ Step 1 – Feature generation script 1 → …
After one month of working on my first real-world ML project, my manager told me: “Pau, we need to stop the project. This is not going anywhere.” I felt like a failure. However, with time I understood the 3 crucial mistakes I made, and transformed them into 3 learnings. 💎 Tip 1: Estimate the Return …
3 things you need to know before your first real-world ML project Read More »
Every aspiring data scientist I talk to thinks their job starts when someone else gives them: a dataset, and a clearly defined metric to optimize for, e.g. accuracy But it doesn’t. It starts with a business problem you need to understand, frame, and solve. This is the key data science skill that separates senior from …
Are you still wondering what the day-to-day of a professional data scientist looks like? What does a data scientist do in the industry? Let me shed some light on this, and share a few tips I learned, that can help you succeed in your job. The problem Despite the colossal amount of educational content on …
Day-to-day of a data scientist: What does a data scientist do? Read More »
Are you a data scientist using CSV files to store your data? What if I told you there is a better way? Have you ever heard of the Parquet file format? Can you imagine a lighter 🦋 faster 🏎️ cheaper 💸 file format to save your datasets? Read this article so you don’t need to …
